Track / Overview

This track addresses the application of Machine Learning and data products in general to business models that share the important aspect of online user interactions, and ultimately depend on the monetization of its user base. These include but are not limited to online media, online advertisement, online games, online marketplaces and classifieds.

Digitalization is completely transforming business models or opens the possibility for completely new and innovative online products. Data and Machine Learning play a central role in this transformation, allowing to build products that customers really want, optimize revenues or build products in which data and Machine Learning are part of the features-set. To this end, understanding the user base and the way the user base interacts with the products is crucial. For example when building recommenders, running targeted marketing campaigns or performing data-driven expansion of content. This is of utmost importance since the right product-user fit is essential to successfully fund a non-tangible online product, either by advertisement, subscriptions or other fees. This track aims to bring Machine Learning practitioners from different areas in online business together who ultimately face the same problems.

Track / Schedule

Bringing ML to Production, what is missing?

With Mikio Braun

Short break

Image Quality of Ebay listings: An ML approach to image scoring for Paid Internet Marketing

With Natalia Golenetskaya

I Want This Product but Different: Generative Methods for Multimodal Data Retrieval

With Ivona Tautkute

A live model for improving data quality in an online shop

With Michael Hardegger


Design, Implementation, and Testing of Personalized News Recommendations at a Large Swiss Newspaper

With Cristina Kadar

Okay doodle, when shall the meeting be scheduled?

With Henrik Grundmann


Increasing the Click-Through-Rate for Cost-Per-Click advertising campaigns

With Dominic Herzog

Dynamic Pricing Competition: Benchmark your Reinforcement Learning Algorithm

With Paul Kleinschmidt

Track / Speakers

Mikio Braun

Staff Data Scientist, GetYourGuide

Henrik Grundmann

Senior Data Scientist, Doodle

Natalia Golenetskaya

Senior Data Scientist, eBay

Michael Hardegger

Lead Machine Learning Engineer, Digitec Galaxus AG

Dominic Herzog

Data Scientist, Tamedia

Ivona Tautkute

Machine Learning Researcher, Tooploox

Cristina Kadar

Senior Data Scientist, NZZ

Paul Kleinschmidt

Data Scientist, Haensel AMS

Nicolas Bär

Senior Data Engineer, Doodle

Track / Co-organizers

Tim Nonner

Chief Data Scientist

Christian Ammendola

Head of Data, Analytics & AI, Neue Züricher Zeitung

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